"""simple docstring"""



from collections import OrderedDict
from typing import List, Mapping

from packaging import version

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


__magic_name__     					=       logging.get_logger(__name__)

__magic_name__     					=       {
    '''google/efficientnet-b7''': '''https://huggingface.co/google/efficientnet-b7/resolve/main/config.json''',
}

class SCREAMING_SNAKE_CASE  (     snake_case__						):







 """simple docstring"""


 a_							:						int	      ='''efficientnet'''


 def __init__( self		:   Any       , _snake_case		:   List[Any] = 3       , _snake_case		:   List[str] = 600       , _snake_case		:   Optional[Any] = 2.0       , _snake_case		:   Optional[int] = 3.1       , _snake_case		:   str = 8       , _snake_case		:   str = [3, 3, 5, 3, 5, 5, 3]       , _snake_case		:   str = [32, 16, 24, 40, 80, 112, 192]       , _snake_case		:   Any = [16, 24, 40, 80, 112, 192, 320]       , _snake_case		:   int = []       , _snake_case		:   Dict = [1, 2, 2, 2, 1, 2, 1]       , _snake_case		:   Tuple = [1, 2, 2, 3, 3, 4, 1]       , _snake_case		:   Tuple = [1, 6, 6, 6, 6, 6, 6]       , _snake_case		:   Optional[int] = 0.25       , _snake_case		:   Optional[int] = "swish"       , _snake_case		:   Tuple = 2560       , _snake_case		:   Optional[Any] = "mean"       , _snake_case		:   Optional[Any] = 0.02       , _snake_case		:   Optional[Any] = 0.001       , _snake_case		:   List[Any] = 0.99       , _snake_case		:   Optional[int] = 0.5       , _snake_case		:   Union[str, Any] = 0.2       , **_snake_case		:   str       , )					->      Dict:




    '''simple docstring'''






    super().__init__(**_UpperCAmelCase					)

    a__  					=		num_channels
    a__  					=		image_size
    a__  					=		width_coefficient
    a__  					=		depth_coefficient
    a__  					=		depth_divisor
    a__  					=		kernel_sizes
    a__  					=		in_channels
    a__  					=		out_channels
    a__  					=		depthwise_padding
    a__  					=		strides
    a__  					=		num_block_repeats
    a__  					=		expand_ratios
    a__  					=		squeeze_expansion_ratio
    a__  					=		hidden_act
    a__  					=		hidden_dim
    a__  					=		pooling_type
    a__  					=		initializer_range
    a__  					=		batch_norm_eps
    a__  					=		batch_norm_momentum
    a__  					=		dropout_rate
    a__  					=		drop_connect_rate
    a__  					=		sum(_UpperCAmelCase					) * 4

class SCREAMING_SNAKE_CASE  (     snake_case__						):







 """simple docstring"""


 a_							:						List[str]	      =version.parse("1.11"						)


 @property
 def 							_lowerCAmelCase					( self		:   int					)					->      Mapping[str, Mapping[int, str]]:




    '''simple docstring'''






    return OrderedDict(
        [
            ('pixel_values', {0: 'batch', 1: 'num_channels', 2: 'height', 3: 'width'}),
        ]					)



 @property
 def 							_lowerCAmelCase					( self		:   Any					)					->      float:




    '''simple docstring'''






    return 1E-5







'''simple docstring'''

import warnings

from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor


SCREAMING_SNAKE_CASE__     :						Optional[Any]	=  logging.get_logger(__name__)

class 							a__( snake_case__     ):






			def __init__(     self					,   *_UpperCAmelCase					,   **_UpperCAmelCase						)							->							None:
					warnings.warn(
					    'The class GLPNFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
					    ' use GLPNImageProcessor instead.'					,   _UpperCAmelCase					,   )
					super().__init__(*_UpperCAmelCase					,   **_UpperCAmelCase						)




